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Big data implementation in Tesla using classification with rapid miner | ||
| International Journal of Nonlinear Analysis and Applications | ||
| دوره 12، Special Issue، اسفند 2021، صفحه 2057-2066 اصل مقاله (979.79 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22075/ijnaa.2021.6016 | ||
| نویسندگان | ||
| Johanes Fernandes Andry1؛ Julia Gunadi1؛ Glisina Dwinoor Rembulan2؛ Hendy Tannady* 3 | ||
| 1Information Systems Department, Universitas Bunda Mulia, Jakarta, Indonesia | ||
| 2Industrial Engineering Department, Universitas Bunda Mulia, Jakarta, Indonesia | ||
| 3Management Department, Kalbis Institute, Jakarta, Indonesia | ||
| تاریخ دریافت: 13 شهریور 1401، تاریخ بازنگری: 22 مهر 1401، تاریخ پذیرش: 05 آذر 1401 | ||
| چکیده | ||
| In this study, we will analyze how big data is implemented in TESLA Company, in this case, we will use sales data. With the growth of big data and the need for its use in companies, nowadays big data is everywhere. TESLA is an American automobile and energy storage company founded by engineers Martin Eberhard and Marc Tarpenning in July 2003 under the name Tesla Motors. The company name is a tribute to inventor and electrical engineer Nikola Tesla. Eberhard said that he wanted to build an automobile manufacturer and also a technology company whose core technology is batteries, computer software and proprietary electric motors. As the amount of data that companies must process today continues to increase, companies must keep up with the times by using big data. Big data can be used to move, contain, and access large amounts of unstructured and disparate data in a timely manner. it is good. The method we use is quantitative data. This calculation will use the Rapid Miner software. The result of this study is the data is 2,146 units, total volume from 118,500 to 47,065,000 based on the number of existing sales, and classification results are from 2621300 to 18766300. | ||
| کلیدواژهها | ||
| Big data؛ Classification؛ Data؛ TESLA | ||
| مراجع | ||
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